Optimizing Paving Block Parameters with Taguchi Method for Higher Compressive Strength: Optimasi Parameter Bata Paving Menggunakan Metode Taguchi untuk Meningkatkan Kekuatan Tekanan - Syarifah, Faranisa Aulia Ar Rahma; Rochmoeljati, Rr. (Indonesian Journal of Innovation Studies, 2025)
General background: The growing demand for high-quality paving blocks in Indonesia requires manufacturers to consistently meet SNI standards, particularly in compressive strength, as it determines durability and safety. Specific background: At PT. XYZ, production inconsistencies often lead to cracks during testing, highlighting variability in process parameters. Knowledge gap: Although the Taguchi method has been widely applied in manufacturing quality improvement, its systematic integration with multiple critical parameters in paving block production remains underexplored. Aim: This study seeks to optimize compressive strength by applying the Taguchi Design of Experiments with an L₉ orthogonal array, focusing on cement–sand ratio, fly ash content, and aggregate size. Results: Signal-to-Noise Ratio and ANOVA analyses revealed that cement–sand ratio is the most influential factor, followed by fly ash and aggregate type, with the optimal combination of 3:5 cement–sand ratio, 3% fly ash, and medium aggregate (5–10 mm), producing a compressive strength of 42.16 MPa—exceeding the SNI minimum of 40 MPa. Novelty: This research introduces a robust model that integrates Taguchi and ANOVA to validate optimal production parameters specifically for paving block manufacturing. Implications: The findings provide practical guidelines for improving product consistency, reducing defects, and supporting cost-effective quality engineering in the paving block industry. Highlights: Taguchi design identified optimal cement–sand ratio, fly ash, and aggregate size. Optimal parameters achieved 42.16 MPa, exceeding SNI standards. Integration of Taguchi and ANOVA ensures consistent, cost-effective quality control. Keywords: Paving Block, Compressive Strength, Taguchi Method, ANOVA, Quality Engineering